SOTAVerified

Optical Flow Estimation

Optical Flow Estimation is a computer vision task that involves computing the motion of objects in an image or a video sequence. The goal of optical flow estimation is to determine the movement of pixels or features in the image, which can be used for various applications such as object tracking, motion analysis, and video compression.

Approaches for optical flow estimation include correlation-based, block-matching, feature tracking, energy-based, and more recently gradient-based.

Further readings:

Definition source: Devon: Deformable Volume Network for Learning Optical Flow

Image credit: Optical Flow Estimation

Papers

Showing 651700 of 2184 papers

TitleStatusHype
Low-light Environment Neural SurveillanceCode0
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action DetectionCode0
Long-term Temporal Convolutions for Action RecognitionCode0
LSMVOS: Long-Short-Term Similarity Matching for Video ObjectCode0
Estimating Nonplanar Flow from 2D Motion-blurred Widefield Microscopy Images via Deep LearningCode0
LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow EstimationCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic SegmentationCode0
Let's Dance: Learning From Online Dance VideosCode0
Compressive Online Robust Principal Component Analysis with Optical Flow for Video Foreground-Background SeparationCode0
Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual OdometryCode0
Event TransformerCode0
Real-Time Image Analysis Software Suitable for Resource-Constrained ComputingCode0
Learning to Steer by Mimicking Features from Heterogeneous Auxiliary NetworksCode0
Complementing Brightness Constancy with Deep Networks for Optical Flow PredictionCode0
Enhancing Action Recognition by Leveraging the Hierarchical Structure of Actions and Textual ContextCode0
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion SegmentationCode0
Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression RecognitionCode0
Learning Task-Specific Generalized Convolutions in the Permutohedral LatticeCode0
End-to-end Video-level Representation Learning for Action RecognitionCode0
Accelerated First Order Methods for Variational ImagingCode0
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field EstimationCode0
Learning Temporal Pose Estimation from Sparsely-Labeled VideosCode0
Learning Optical Expansion From Scale MatchingCode0
Learning on the Edge: Explicit Boundary Handling in CNNsCode0
End-to-End Learning of Representations for Asynchronous Event-Based DataCode0
End-to-End Learning of Motion Representation for Video UnderstandingCode0
Learning Multi-Human Optical FlowCode0
Learning End-To-End Scene Flow by Distilling Single Tasks KnowledgeCode0
Learning Dynamic Point Cloud Compression via Hierarchical Inter-frame Block MatchingCode0
Learning Energy Based Inpainting for Optical FlowCode0
EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion SaliencyCode0
Kinematics Modeling Network for Video-based Human Pose EstimationCode0
Deep Motion Blind Video StabilizationCode0
Learning Correspondence from the Cycle-Consistency of TimeCode0
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on VideoCode0
Learning Human Optical FlowCode0
LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance ImagingCode0
Co-attention Propagation Network for Zero-Shot Video Object SegmentationCode0
A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame PredictionCode0
Learnable Cost Volume Using the Cayley RepresentationCode0
Lagrangian Motion Magnification with Double Sparse Optical Flow DecompositionCode0
Ego-motion Estimation Based on Fusion of Images and EventsCode0
KORSAL: Key-point Detection based Online Real-Time Spatio-Temporal Action LocalizationCode0
Joint Detection of Motion Boundaries and OcclusionsCode0
Iterative Residual Refinement for Joint Optical Flow and Occlusion EstimationCode0
InterpoNet, A brain inspired neural network for optical flow dense interpolationCode0
Exploring Temporal Information for Improved Video UnderstandingCode0
Kernel learning for visual perceptionCode0
Learning Blind Video Temporal ConsistencyCode0
Show:102550
← PrevPage 14 of 44Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error6.64Unverified
2FastFlowNet-ftAverage End-Point Error4.89Unverified
3UnrolledCostAverage End-Point Error4.69Unverified
4LiteFlowNet-ftAverage End-Point Error4.54Unverified
5FlowNet2Average End-Point Error3.96Unverified
6IRR-PWCAverage End-Point Error3.84Unverified
7SelFlowAverage End-Point Error3.74Unverified
8FDFlowNet-ftAverage End-Point Error3.71Unverified
9ScopeFlowAverage End-Point Error3.59Unverified
10LiteFlowNet2-ftAverage End-Point Error3.48Unverified
#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error8.36Unverified
2FastFlowNet-ftAverage End-Point Error6.08Unverified
3UnrolledCostAverage End-Point Error5.8Unverified
4LiteFlowNet-ftAverage End-Point Error5.38Unverified
5MR-FlowAverage End-Point Error5.38Unverified
6FDFlowNet-ftAverage End-Point Error5.11Unverified
7LiteFlowNet2-ftAverage End-Point Error4.69Unverified
8IRR-PWCAverage End-Point Error4.58Unverified
9LiteFlowNet3-SAverage End-Point Error4.53Unverified
10ContinualFlow + ftAverage End-Point Error4.52Unverified
#ModelMetricClaimedVerifiedStatus
1PWC-NetF1-all33.7Unverified
2FastFlowNetF1-all33.1Unverified
3FlowNet2F1-all30Unverified
4VCNF1-all25.1Unverified
5HD3F1-all24Unverified
6MaskFlowNetF1-all23.1Unverified
7SCVF1-all19.3Unverified
8RAPIDFlowF1-all17.7Unverified
9CRAFTF1-all17.5Unverified
10RAFTF1-all17.4Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftFl-all11.22Unverified
2UnrolledCostFl-all10.81Unverified
3LiteFlowNet-ftFl-all9.38Unverified
4SelFlowFl-all8.42Unverified
5IRR-PWCFl-all7.65Unverified
6LiteFlowNet2-ftFl-all7.62Unverified
7LiteFlowNet3Fl-all7.34Unverified
8LiteFlowNet3-SFl-all7.22Unverified
9MaskFlownet-SFl-all6.81Unverified
10RAPIDFlowFl-all6.12Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftAverage End-Point Error1.8Unverified
2IRR-PWCAverage End-Point Error1.6Unverified
3LiteFlowNet-ftAverage End-Point Error1.6Unverified
4PWC-Net + ft - axXivAverage End-Point Error1.5Unverified
5FDFlowNet-ftAverage End-Point Error1.5Unverified
6SelFlowAverage End-Point Error1.5Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4Unverified
8LiteFlowNet3Average End-Point Error1.3Unverified
9LiteFlowNet3-SAverage End-Point Error1.3Unverified
10MaskFlownet-SAverage End-Point Error1.1Unverified
#ModelMetricClaimedVerifiedStatus
1PWCNet1px total82.27Unverified
2SPyNet1px total29.96Unverified
3GMFlow1px total10.36Unverified
4GMA1px total7.07Unverified
5RAFT1px total6.79Unverified
6FlowNet21px total6.71Unverified
7FlowFormer1px total6.51Unverified
8MS-RAFT+1px total5.72Unverified
9RPKNet1px total4.81Unverified
10DPFlow1px total3.44Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error5.21Unverified
2MDFlow-FastAverage End-Point Error4.73Unverified
3UpFlowAverage End-Point Error4.68Unverified
4ARFlow-MVAverage End-Point Error4.49Unverified
5MDFlowAverage End-Point Error4.16Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error6.5Unverified
2MDFlow-FastAverage End-Point Error5.99Unverified
3ARFlow-MVAverage End-Point Error5.67Unverified
4MDFlowAverage End-Point Error5.46Unverified
5UpFlowAverage End-Point Error5.32Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVFl-all11.79Unverified
2MDFlow-FastFl-all11.43Unverified
3UpFlowFl-all9.38Unverified
4MDFlowFl-all8.91Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVAverage End-Point Error1.5Unverified
2UpFlowAverage End-Point Error1.4Unverified